About the Team

The Finance & Supply Chain Engineering organization includes two complementary teams. Software Engineering builds internal full-stack applications, durable agentic workflows, plugins, MCPs, and measurable AI-enabled engineering practices. Data Engineering builds trusted analytics data assets for Finance and Supply Chain. The teams have distinct charters, with important shared dependencies and broad cross team partnerships across Engineering, Applications, Finance, and Supply Chain.

About the Role

We are looking for a hands-on senior technical leader who will report alongside the Software Engineering and Data Engineering managers. This is an individual-contributor role with no immediate people-management responsibility. The Tech Lead will raise the technical bar across both teams, participate in important cross-team or high-risk design decisions, and directly own and ship high-impact work. The role should improve team judgment and autonomy rather than act as a floating architect or universal approval gate.
In this role, you will:

• Partner with the Software Engineering and Data Engineering managers as a peer technical leader; managers retain accountability for people, staffing, priorities, performance, and delivery commitments.

• Directly own the architecture, implementation, launch, and operation of one or more high-impact initiatives, remaining accountable for real outcomes rather than advisory output alone.

• Guide important design decisions that are cross-team, difficult to reverse, or material to security, financial controls, reliability, data quality, or long-term cost of ownership.

• Establish pragmatic engineering standards across architecture, APIs and data contracts, testing, security, reliability, observability, lineage, data quality, and operational ownership.

• Advance engineering standards for building with AI, including agentic workflows, evaluation, telemetry, adoption, and outcome measurement.

• Work across backend, full-stack, data, and big-data systems, making sound boundary decisions and bringing the right domain experts into the design.

• Partner deeply with Engineering, Applications, Product, Finance, Supply Chain, Security, and other stakeholders to translate ambiguous needs into durable technical systems.

• Raise the technical capability of both teams through design reviews, code reviews, mentoring, written guidance, and reusable reference implementations.

• Protect team autonomy: focus involvement on consequential decisions, clarify principles and tradeoffs, and avoid becoming a required approver for routine or reversible work.

You might thrive in this role if you:

• Have significant professional engineering experience with sustained staff-level or equivalent impact as an individual contributor; prior people management is not required, but a plus.

• Can reason across a full-stack application—from user experience and client architecture through backend services, integrations, authorization, and durable state.

• Have strong data-engineering judgment across analytical modeling, batch or streaming pipelines, orchestration, lineage, quality, scale, and downstream data contracts.

• Have personally designed, built, shipped, and operated consequential systems, and can go from architecture to implementation details without relying on positional authority.

• Have led important technical decisions and cross-team initiatives through influence, clear reasoning, and trusted partnership.

• Care deeply about correctness, security, data quality, auditability, operational excellence, and measurable outcomes.

• Communicate clearly with engineers, managers, and non-technical partners; lead with context and principles rather than control.

Nice to Have:

• Experience building internal products, developer platforms, workflow systems, or analytics platforms used across multiple teams.

• Experience with LLM applications, durable agents, AI evaluations, plugins, MCPs, or measurement of AI-enabled engineering outcomes.

• Experience in Finance, Supply Chain, accounting, procurement, ERP, or another domain where controls, reconciliation, and traceability matter.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. 

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.

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